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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research

Research Programs and Projects at this Location

ARS research is organized into National Programs. Within each National Program are research projects. Listed below are  the National Programs and research projects currently conducted at this location.

Clicking on a National Program (NP) will take you  to the main ARS site for more information on the program. Clicking on a research  project title will take you to more information on the project.


Current View: All Projects

Show All Projects || Appropriated Projects Only

Plant Genetic Resources, Genomics and Genetic Improvement (NP #301)
Genetic Improvement and Nutritional Qualities of Pulse Crops
(In-House Appropriated)
Sugar Beet Genetics and Pathogen Interactions
(In-House Appropriated)
Development of Fungicide Resistance Monitoring Tools for Botrytis Spp.
(Cooperative Agreement)
Development, Validation and Application of Fungicide Resistance Monitoring Tools for Botrytis Spp. of Specialty Crops
(Cooperative Agreement)
Organic Bean Processing Quality and Outreach
(Cooperative Agreement)
Cultivar Development: Accelerating Cultivar Release for Several Dry Bean Market Classes Using Genomic Selection
(Interagency Reimbursable Agreement)
Development, Validation, and Deployment of Fungicide Resistance Markers for Botrytis Induced Diseases of Specialty Crops
(Reimbursable Cooperative Agreement)
Accessible Cultivar and Processing Strategies for Improved Pulse Flour Quality
(Non-Assistance Cooperative Agreement)
Development of a Genomic Selection Model for Rhizoctonia Root and Crown Rot Resistance Across ARS Breeding Programs
(Non-Assistance Cooperative Agreement)
Dry Bean Dehulling Method Development
(Non-Assistance Cooperative Agreement)
Off-Flavors in Pulse Flours
(Non-Assistance Cooperative Agreement)
Pinto Bean Flour Quality
(Non-Assistance Cooperative Agreement)
Pulse Flour Lipid Profiling
(Non-Assistance Cooperative Agreement)
Product Quality and New Uses (NP #306)
Automated Technologies for Harvesting and Quality Evaluation of Fruits and Vegetables
(In-House Appropriated)
Deep Learning-based 3D Fruit-Tree Perception Through Efficient Multi-Sensor Fusion for Robotic Harvesting of Apples
(Non-Assistance Cooperative Agreement)
Development of a Control and Planning System for an Apple Robotic Harvester
(Non-Assistance Cooperative Agreement)
Development of a Fast, Cost-effective Approach for Quantification of Microbial Community Shift in Chitin Amended Soil
(Non-Assistance Cooperative Agreement)